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Record W4281807112 · doi:10.1038/s41467-022-31082-0

Parallel ventral hippocampus-lateral septum pathways differentially regulate approach-avoidance conflict

2022· article· en· W4281807112 on OpenAlexafffund
Dylan C.M. Yeates, Dallas Leavitt, Sajeevan Sujanthan, Nisma Khan, Denada Alushaj, Andy Lee, Rutsuko Ito

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest HospitalThe Scarborough HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsNeuroscienceInhibitory postsynaptic potentialHippocampusPsychologyBiology

Abstract

fetched live from OpenAlex

The ability to resolve an approach-avoidance conflict is critical to adaptive behavior. The ventral CA3 (vCA3) and CA1 (vCA1) subfields of the ventral hippocampus (vHPC) have been shown to facilitate avoidance and approach behavior, respectively, in the face of motivational conflict, but the neural circuits by which this subfield-specific regulation is implemented is unknown. We demonstrate that two distinct pathways from these subfields to lateral septum (LS) contribute to this divergent control. In Long-Evans rats, chemogenetic inhibition of the vCA3- LS caudodorsal (cd) pathway potentiated approach towards a learned conflict-eliciting stimulus, while inhibition of the vCA1-LS rostroventral (rv) pathway potentiated approach non-specifically. Additionally, vCA3-LScd inhibited animals were less hesitant to explore food during environmental uncertainty, while the vCA1- LSrv inhibited animals took longer to initiate food exploration. These findings suggest that the vHPC influences multiple behavioral systems via differential projections to the LS, which in turn send inhibitory projections to motivational centres of the brain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.091
GPT teacher head0.307
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2022
Admission routes2
Has abstractyes

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Same venueNature CommunicationsSame topicMemory and Neural MechanismsFrench-language works237,207